Language:
English
繁體中文
Help
Login
Back
Switch To:
Labeled
|
MARC Mode
|
ISBD
SQL Server Big Data Clusters = Earl...
~
van de Laar, Enrico.
SQL Server Big Data Clusters = Early First Edition Based on Release Candidate 1 /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
SQL Server Big Data Clusters / by Benjamin Weissman, Enrico van de Laar.
Reminder of title:
Early First Edition Based on Release Candidate 1 /
Author:
Weissman, Benjamin.
other author:
van de Laar, Enrico.
Description:
XV, 246 p. 189 illus.online resource. :
Contained By:
Springer Nature eBook
Subject:
Database management. -
Online resource:
https://doi.org/10.1007/978-1-4842-5110-2
ISBN:
9781484251102
SQL Server Big Data Clusters = Early First Edition Based on Release Candidate 1 /
Weissman, Benjamin.
SQL Server Big Data Clusters
Early First Edition Based on Release Candidate 1 /[electronic resource] :by Benjamin Weissman, Enrico van de Laar. - 1st ed. 2019. - XV, 246 p. 189 illus.online resource.
1. What Are Big Data Clusters? -- 2. Big Data Cluster Architecture -- 3. Installation, Deployment, and Management of Big Data Clusters -- 4. Loading Data into Big Data Clusters -- 5. Querying Big Data Clusters through T-SQL -- 6. Working with Spark in Big Data Clusters -- 7. Machine Learning on Big Data Clusters -- 8. Create and Consume Big Data Cluster Apps.
Get a head-start on learning one of SQL Server 2019’s latest and most impactful features—Big Data Clusters—that combines large volumes of non-relational data for analysis along with data stored relationally inside a SQL Server database. This book provides a first look at Big Data Clusters based upon SQL Server 2019 Release Candidate 1. Start now and get a jump on your competition in learning this important new feature. Big Data Clusters is a feature set covering data virtualization, distributed computing, and relational databases and provides a complete AI platform across the entire cluster environment. This book shows you how to deploy, manage, and use Big Data Clusters. For example, you will learn how to combine data stored on the HDFS file system together with data stored inside the SQL Server instances that make up the Big Data Cluster. Filled with clear examples and use cases, this book provides everything necessary to get started working with Big Data Clusters in SQL Server 2019 using Release Candidate 1. You will learn about the architectural foundations that are made up from Kubernetes, Spark, HDFS, and SQL Server on Linux. You then are shown how to configure and deploy Big Data Clusters in on-premises environments or in the cloud. Next, you are taught about querying. You will learn to write queries in Transact-SQL—taking advantage of skills you have honed for years—and with those queries you will be able to examine and analyze data from a wide variety of sources such as Apache Spark. Through the theoretical foundation provided in this book and easy-to-follow example scripts and notebooks, you will be ready to use and unveil the full potential of SQL Server 2019: combining different types of data spread across widely disparate sources into a single view that is useful for business intelligence and machine learning analysis. You will: Install, manage, and troubleshoot Big Data Clusters in cloud or on-premise environments Analyze large volumes of data directly from SQL Server and/or Apache Spark Manage data stored in HDFS from SQL Server as if it were relational data Implement advanced analytics solutions through machine learning and AI Expose different data sources as a single logical source using data virtualization.
ISBN: 9781484251102
Standard No.: 10.1007/978-1-4842-5110-2doiSubjects--Topical Terms:
557799
Database management.
LC Class. No.: QA76.9.D3
Dewey Class. No.: 005.74
SQL Server Big Data Clusters = Early First Edition Based on Release Candidate 1 /
LDR
:03999nam a22003975i 4500
001
1006402
003
DE-He213
005
20200702013319.0
007
cr nn 008mamaa
008
210106s2019 xxu| s |||| 0|eng d
020
$a
9781484251102
$9
978-1-4842-5110-2
024
7
$a
10.1007/978-1-4842-5110-2
$2
doi
035
$a
978-1-4842-5110-2
050
4
$a
QA76.9.D3
072
7
$a
UN
$2
bicssc
072
7
$a
COM021000
$2
bisacsh
072
7
$a
UN
$2
thema
072
7
$a
UMT
$2
thema
082
0 4
$a
005.74
$2
23
100
1
$a
Weissman, Benjamin.
$e
author.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1299941
245
1 0
$a
SQL Server Big Data Clusters
$h
[electronic resource] :
$b
Early First Edition Based on Release Candidate 1 /
$c
by Benjamin Weissman, Enrico van de Laar.
250
$a
1st ed. 2019.
264
1
$a
Berkeley, CA :
$b
Apress :
$b
Imprint: Apress,
$c
2019.
300
$a
XV, 246 p. 189 illus.
$b
online resource.
336
$a
text
$b
txt
$2
rdacontent
337
$a
computer
$b
c
$2
rdamedia
338
$a
online resource
$b
cr
$2
rdacarrier
347
$a
text file
$b
PDF
$2
rda
505
0
$a
1. What Are Big Data Clusters? -- 2. Big Data Cluster Architecture -- 3. Installation, Deployment, and Management of Big Data Clusters -- 4. Loading Data into Big Data Clusters -- 5. Querying Big Data Clusters through T-SQL -- 6. Working with Spark in Big Data Clusters -- 7. Machine Learning on Big Data Clusters -- 8. Create and Consume Big Data Cluster Apps.
520
$a
Get a head-start on learning one of SQL Server 2019’s latest and most impactful features—Big Data Clusters—that combines large volumes of non-relational data for analysis along with data stored relationally inside a SQL Server database. This book provides a first look at Big Data Clusters based upon SQL Server 2019 Release Candidate 1. Start now and get a jump on your competition in learning this important new feature. Big Data Clusters is a feature set covering data virtualization, distributed computing, and relational databases and provides a complete AI platform across the entire cluster environment. This book shows you how to deploy, manage, and use Big Data Clusters. For example, you will learn how to combine data stored on the HDFS file system together with data stored inside the SQL Server instances that make up the Big Data Cluster. Filled with clear examples and use cases, this book provides everything necessary to get started working with Big Data Clusters in SQL Server 2019 using Release Candidate 1. You will learn about the architectural foundations that are made up from Kubernetes, Spark, HDFS, and SQL Server on Linux. You then are shown how to configure and deploy Big Data Clusters in on-premises environments or in the cloud. Next, you are taught about querying. You will learn to write queries in Transact-SQL—taking advantage of skills you have honed for years—and with those queries you will be able to examine and analyze data from a wide variety of sources such as Apache Spark. Through the theoretical foundation provided in this book and easy-to-follow example scripts and notebooks, you will be ready to use and unveil the full potential of SQL Server 2019: combining different types of data spread across widely disparate sources into a single view that is useful for business intelligence and machine learning analysis. You will: Install, manage, and troubleshoot Big Data Clusters in cloud or on-premise environments Analyze large volumes of data directly from SQL Server and/or Apache Spark Manage data stored in HDFS from SQL Server as if it were relational data Implement advanced analytics solutions through machine learning and AI Expose different data sources as a single logical source using data virtualization.
650
0
$a
Database management.
$3
557799
650
0
$a
Microsoft software.
$3
1253736
650
0
$a
Microsoft .NET Framework.
$3
565417
650
0
$a
Big data.
$3
981821
650
1 4
$a
Database Management.
$3
669820
650
2 4
$a
Microsoft and .NET.
$3
1114109
650
2 4
$a
Big Data.
$3
1017136
700
1
$a
van de Laar, Enrico.
$e
author.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1261149
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer Nature eBook
776
0 8
$i
Printed edition:
$z
9781484251096
776
0 8
$i
Printed edition:
$z
9781484251119
856
4 0
$u
https://doi.org/10.1007/978-1-4842-5110-2
912
$a
ZDB-2-CWD
912
$a
ZDB-2-SXPC
950
$a
Professional and Applied Computing (SpringerNature-12059)
950
$a
Professional and Applied Computing (R0) (SpringerNature-43716)
based on 0 review(s)
Multimedia
Reviews
Add a review
and share your thoughts with other readers
Export
pickup library
Processing
...
Change password
Login